Unsupervised Extraction of Workplace Rights and Duties from Collective Bargaining Agreements

被引：3

作者：

Ash, Elliott ^{[1
]}

Jacobs, Jeff ^{[2
]}

MacLeod, Bentley ^{[2
]}

Naidu, Suresh ^{[2
]}

Stammbach, Dominik ^{[1
]}

机构：

[1] Swiss Fed Inst Technol, Zurich, Switzerland

[2] Columbia Univ, New York, NY 10027 USA

来源：

20TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW 2020) | 2020年

关键词：

Unsupervised Extraction; Information Mining; Legal Corpus Analysis;

D O I：

10.1109/ICDMW51313.2020.00112

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper describes an unsupervised legal document parser which performs a decomposition of labor union contracts into discrete assignments of rights and duties among agents of interest. We use insights from deontic logic applied to modal categories and other linguistic patterns to generate topic-specific measures of relative legal authority. We illustrate the consistency and efficiency of the pipeline by applying it to a large corpus of 35K contracts and validating the resulting outputs.

引用

页码：766 / 774

页数：9

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